From: treon3verdery@gmail.com   
      
   the King’s Holly has lived 1.46 million days thus far, other trees have a   
   lifespan of just 3650 days, ceasing to be alive even before a human reaches   
   puberty;  Finding longevity drugs based on the 400,000 percent different   
   longevity difference between    
   trees goes with doing HPLC, something better than electrophoresis like laser   
   spectroscopy, electrophoresis or some other thing, to find all the chemicals,   
   proteins, peptides, lipids, in the plants, as well as at human tissue, then   
   finding those chemicals,   
    proteins, peptides, lipids difference between the 1.46 million day longevity   
   plant, the 3650 day plant, and the human;    
      
      
      
   I read humans share 60% of their genome with the banana, that suggests some   
   plant genes, and plant gene products, and the amount of those chemical plant   
   gene products, have most longevizing molecule versions that can be quantified   
   as to longevity effects    
   at yeast and mice;   
      
       
      
   finding longevity chemicals: the group of chemicals (and genes) at both the   
   (3650 day tree and the human) that are different than the chemicals that the   
   (kings holly and the human share) are places where the chemicals (and the   
   genes) at the humans could    
   improve and the king’s holly is the source of improvement;   
      
      
      
   At homologous genes an organisms that noticed it had the 3650 day plant   
   version rather than the kings holly would notice an opportunity to have more   
   longevizing chemicals endogenously produced   
      
      
      
   finding longevity chemicals: dosing yeast and mice with the chemical that the   
   kings holly gene makes, that the human does not, noting the homologous but   
   different gene, could find longevity drugs;    
      
      
      
   engineering mice and yeast to make that shared homologous kings holly gene   
   then finding out if it longevizes them produces new longevity genes   
      
      
      
   This same approach works for finding longevizing chemicals between groups like   
   million year lifespan endoliths comparison grouped with similar-to-endolith   
   with different habitat organisms with 365 day lifespans, 214 year old whales,   
   and whales with    
   briefer lifespans, 400 year lifespan clams, and clams with annual lifespans,   
   and supercentenarian humans with 18 year marmosets;     
      
      
      
   The genes and gene products (chemicals) that the 400 year clam shares with the   
   annual clam are ignored when narrowing the list of chemicals and genes at the   
   human to find 400 year clam genes with longevity effects;   
      
      
      
   Now, although the amount of the chemicals matters the same thing can be done   
   with chemicals, proteins, peptides, and lipids at the bodies of the various   
   trees and other organisms   
      
      
      
   If the chemical is the the 3650 day plant and the king’s holly, ignore it,   
   if it is only at the king’s holly put it in a database;   
      
      
      
   This works better at varieties of the same species with widely varying   
   lifespans, if there are any species that interbreed but have 2-4 times   
   different longevity, then ignoring the chemicals they share, then making a   
   database of the chemicals only at the    
   long lived variety, then at humans finding if any of the database chamicals    
      
      
      
   There is a thing here though that kind of makes it improvable, for each 14   
   million chemicals the kings holly contains, and the 3650 plant overlaps 90% of   
   them, that is still 1.4 million chemicals that might have longevity effects;   
      
      
      
   I think geneticists who write computer programs already know all about this,   
   but if you have like 100 groups of related-organisms pairs (king’s holly   
   3650 day tree),(mouse, beaver), (214 year whale, less longevity whale),   
   (human, primate with 1/5th    
   human lifespan) with the group members as far apart as possible as to   
   longevity, and then compare the amount the very different most long lived   
   species converge towards each others gene versions, notably moving away from   
   their species-similar organisim,    
   then you find a possible math convergence around better versions of genes, or   
   better versions of physiochemicals   
      
      
      
   The high longevity organisms at each of the 100 bowls of 2 or 3 longevity   
   heterogenous organisms each    
      
      
      
   This technique can be used for other things like, 100 bowls of 2 or 3 mammals   
   each, and the species similar mammals differ as much as possible on behavior,   
   then you look at how the bowl leaders (of very different species) converge on   
   various    
   characteristics, these can be genes, fMRI of brain areas, even things like   
   parenting styles;  a human, or niftily, a deep learning AI can then make a   
   list of trends   
      
      
      
   (Mathematically you would expect the beaver to be more like the mouse, but if   
   the beaver is more like the whale, the human, and the King’s holly then   
   there might be a longevity trend at that homologous gene, similarly you might   
   expect a human to be    
   more like a marmoset than a whale or the king’s holly, but at genes where   
   the king’s holly is more similar that could suggest a “different chemical   
   is better” trend, then noting the upper longevity organisms at each of the   
   100 bowls each with two    
   or three species in them (mouse beaver, 214 year whale, less longevized whale)   
   (longevized bat, less longevized bat) (human, primate with 1/5th human   
   longevity)   
      
      
      
   The 100 bowls of three high distalness (long lived, otherwise) yet each bowl   
   with similar species could be repeated at species that have particularly wide   
   longevity ranges, perhaps birds as well; if this finds a longevity trend for a   
   group of genes at    
   very different birds, then the genes the different bowl gnes most share   
      
      
      
   also the 100 bowls thing of 2 or 3 organisms thing works with longevity   
   chemicals as well, if 100 bowls find like 5000 circulatory chemicals shared at   
   the long lived organisms out of each bowl, then those 5000 chemicals are   
   compared to the chemicals in a    
   human, any of the 100 bowl shared longevity chemicals the human does not (yet)   
   have could be tested on yeast and mice and human tissue culture to find out if   
   they are longevizing; this works with homologous genes as well, if you have   
   100 bowls of clams,    
   birds, sharks, endoliths, plants, and other things, and the distal organisms   
   in each bowl have and above-chance occurence of shared genes, then those could   
   be longevity genes and a human would compare their genome to that shared at   
   the 100 bowls of very    
   different species;  mathematically it would be possible to list in order the   
   genes shared between bowls, and the longevity trend of just that group of   
   bowl-set organisims, so it would be possible to find the likely most   
   longevizing versions of the bowl-   
   shared genes;   
      
      
      
      
   [continued in next message]   
      
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